The document provides information on various textile calculations related to fibre fineness, yarn counts, conversions between different count systems, and calculations for processes like blowroom, carding, drawframe, speedframe, ringframe, winding, warping, and sizing. It includes formulas for calculating production rates, drafts, twists, strengths, efficiencies, and other important metrics for these textile processes. Conversion tables are also provided for weights, linear measures, yarn counts and other units.
Analysis of rejected ring cops in autoconer winding machineTaukir Kabir Tusar
This work describes the causes of rejections of rejected ring cops in autoconer winding machine with assessment of various experimental datas from various quality instruments . This causes includes count variation , co efficient of variation (CV%) , Thick and thin places , neps , slubs , hairiness and some miscellunous causes like oil stained yarns , crackers in yarns , half and excess full cops , coca cola shaped cops etc . This work also suggest a few ways to solve the problems and to reduce the rejection rate of cops in an acceptable range . Sufficient amount of figures and graphs are also included here to make this work more accurate .
Analysis of rejected ring cops in autoconer winding machineTaukir Kabir Tusar
This work describes the causes of rejections of rejected ring cops in autoconer winding machine with assessment of various experimental datas from various quality instruments . This causes includes count variation , co efficient of variation (CV%) , Thick and thin places , neps , slubs , hairiness and some miscellunous causes like oil stained yarns , crackers in yarns , half and excess full cops , coca cola shaped cops etc . This work also suggest a few ways to solve the problems and to reduce the rejection rate of cops in an acceptable range . Sufficient amount of figures and graphs are also included here to make this work more accurate .
Opening in blow room means opening into small flocks. Technological operation of opening means the volume of the flock is increased while the number of fibres remains constant
The compact spinning is a process where fiber strand drawn by drafting system is condensed before twisting it.Following methods are used by machine manufacturers to condense the fiber strand.
1. Aerodynamic condensing.
2. Mechanical condensing.
3. Magnetic condensing.
Compact spinning has a promising future because of the higher production and improved quality of compact yarns
Opening in blow room means opening into small flocks. Technological operation of opening means the volume of the flock is increased while the number of fibres remains constant
The compact spinning is a process where fiber strand drawn by drafting system is condensed before twisting it.Following methods are used by machine manufacturers to condense the fiber strand.
1. Aerodynamic condensing.
2. Mechanical condensing.
3. Magnetic condensing.
Compact spinning has a promising future because of the higher production and improved quality of compact yarns
Your expert interior designs cost effectively visualized the way you want themLifang Digital UK Ltd
Currently visualizing interior designs for a tower apartment complex in a new city in Lagos, Nigeria. The CGI's are part of a wider project scope that we are working on directly with the Developers interior designers and architects there.
Great Ideas! 2013 Idea Lab
Making Ideas Happen: A Strengths-Based Learning Experience
Don’t let your flash of brilliance fade away. Learn by doing in this session by taking the Appreciative Inquiry and G.R.O.W. methods out for a spin to better refine your great idea and articulate next steps to make it happen. Harness the support of your colleagues and community to bring your idea to life, and walk away with a plan to move your idea forward despite the resistance you might face.
Do you know why a budget is so important? On the surface it seems like creating a budget is just a tedious financial exercise. But you might be surprised at just how valuable a budget can be. This ppt might help u to know the basics
Platoon Control of Nonholonomic Robots using Quintic Bezier SplinesKaustav Mondal
In this project, quintic polynomials were used to perform platooning in nonholonomic robots. Both hardware and simulations results have been presented.
Vertical Screw Conveyor Design Project for MEX5277 - Machine Design
Step by step guide on how to create a Vertical Screw Conveyor.
Power calculation of a vertical screw conveyor.
Spin plan for the spinning mill. Here the calculation is done for 80s Ne combed cotton yarn. for carded yarn, the calculation for comber and lap former is not needed.
Design of an automotive differential with reduction ratio greater than 6eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Analytical Optimization of Chassis Frame for 40ft Dual-Axle Flatbed Trailer D...IOSR Journals
This article will review a design and analysis study that reduces trailer chassis mass while
minimizing the total cost impact. Design approaches, material selections and proposed section were reviewed.
The Trailer chassis main member were quantified and summarized to create an overall mass and weighted cost
estimate for a low mass Trailer.
Abstract:This paper describes about the design and fabrication of various parts of a groundnut decorticator/ sheller. Overall, this machine involves processes like design, fabrication and assembly of different components etc. In India, Agriculture is the backbone. In India, groundnut is grown on a small scale by farmer. The major hurdle in the groundnut production in India is the inavailability or lack of groundnut processing machines available to farmer. In the beginning the peanuts were separated from its shells by the workers manually. The output from this method was very less and could not satisfy the market demand as it was very time taking process. Research-work for design, manufacture, and performance evaluation of a groundnut decorticator/sheller consisting of feeder hopper with a flow rate control device, shelling unit, separating unit and power system. Our main intension was to make such a machine, whose productivity is high & machine gets operated on 1 H.P. electric. The fresher and small farmer or business man can start business by investing less capital.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
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TEXTILE CALCULATIONS
FIBRE FINENESS, YARN COUNTS AND CONVERSIONS
Micronaire Value (Cotton) : The unit is micrograms per inch. The average weight of one inch
length of fibre, expressed in micrograms(0.000001 gram).
Denier (Man-Made Fibres) : Weight in grams per 9000 meters of fibre.
Micron (Wool) : Fineness is expressed as fibre diameter in microns(0.001mm)
Conversions:
· Denier = 0.354 x Micronaire value
· Micronaire value = 2.824 x Denier
YARN COUNTS
It is broadly classified into;
1. DIRECT SYSTEM
2. INDIRECT SYSTEM
INDIRECT SYSTEM
· English count (Ne)
· French count(Nf)
· Metric count(Nm)
· Worsted count
Metric system: Metric count(Nm) indicates the number of 1 kilometer(1000 meter) lengths per
Kg.
Nm = length in Km / weight in kg (or)
Nm = length meter / weight in grams
DIRECT SYSTEM
· Tex count
· Denier
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CONVERSION TABLE FOR YARN COUNTS
Tex Den Nm Grains/yd
Tex den/9 1000/Nm gr.yd x 70.86
Ne 590.54/tex 5314.9/den Nm x .5905 8.33 / gr/yd
Den tex x 9 9000/Nm gr/yd x 637.7
Nm 1000/tex 9000/den 14.1 / gr/yd
Grains/yd tex / 70.86 den / 637.7 14.1/Nm
Where, Nm – metric count, Nec – cotton count
CONVERSION TABLE FOR WEIGHTS
Ounce Grains Grams Kilograms Pounds
Ounce 437.5 grains 28.350 grams
Grains
0.03527
ounces
0.0648 grams
Grams 0.03527 grains 15.432 grains 0.001 kgs
Kilograms 35.274 ounces 15432 grains 1000 grams
2.2046
pounds
Pounds 16.0 ounces 7000 grains 453.59 grams 0.4536 kgs
CONVERSION TABLE FOR LINEAR MEASURES
Yard Feet Inches Centimeter Meter
Yard 3 feet 36 inches 91.44 cms
0.9144
meter
Feet 0.3333 yards 12 inches 30.48 cms
0.3048
meter
Inches 0.0278 yards 0.0833 feet 2.54 cms
0.254
meter
Centimeter 0.0109 yards 0.0328 feet 0.3937 inches 0.01meter
Meter 1.0936 yards 3.281 feet 39.37 inches 100 cms
CALCULATIONS
Grams per meter = 0.5905 / Ne
Grams per yard = 0.54 / Ne
Tex = den x .11 = 1000/Nm = Mic/25.4
Ne = Nm/1.693
DRAFT = (feed weight in g/m) / (delivery weight in g/m)
DRAFT = Tex (feed) / Tex(delivery)
DRAFT = delivery roll surface speed / feed roll surface speed
No of hanks delivered by m/c = (Length delivered in m/min) / 1.605
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BLOW ROOM
% trash in cotton - % trash in lap
(1) Blow-room Cleaning Efficiency% (CE) = -------------------------------------------
% trash in cotton
(2) Lint in waste (%) = 100 - CE
CARDING
(1) P =( L x 1.0936 x 60 x Effy ) / (Hank (Ne) x 36 x 840 x 2.2045)
P - production in kgs / hr
L - delivery speed in m/min
effy- efficiency
Ne - English count ( number of 840 yards in one pound)
840 - constant
2.2045- to convert from lbs to kilograms
(2) Production In Kgs / Hr = (L x Ktex x 60 x Effy) / ( 1000)
L - delivery speed in m/min
Ktex- sliver count in Ktex (kilotex)
effy - efficiency
1000- to convert to kilograms from grams
(3) Production In Kgs / 8 Hrs = (0.2836 x L x Effy) / (Ne)
L - delivery speed in m/min
effy - efficiency
Ne - English count
(4) Prodn / 8 Hrs = (Hank x Nd) /( Ne x 2.2045)
Hank = no of hank (840 yards)delivered by the machine
Nd = no of deliveries
Ne = hank of the material
(5) Total Draft in Card = (Feed Weight in g/m) / (Sliver Weight in g/m)
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Wt. per yard of lap fed
(6) Actual draft = ------------------------------------------------
Wt. per yard of card sliver delivered
Length of card sliver delivered
(7) Mechanical draft = ----------------------------------------
Length of lap fed
or
Draft constant of card machine
= ------------------------------------------
Draft change pinion
(8) Actual draft is always greater than the mechanical draft in carding because it is the
carding waste% that increases the actual draft.
DRAWFRAME
(1) Break Draft = Surface Speed of 2nd Roller / Surface Speed of Back Roller
(2) Main Draft = Surface Speed of 1st Roller / Surface Speed of 2nd (Middle)
Roller
(3) Total Draft = Surface speed of delivery roller / surface of feed roller
(4) Production In Kgs / 8 Hrs = (0.2836 x L x Effy x Nd) / (Ne)
L - delivery speed in m/min
effy - efficiency
Ne - english count
Nd - No of delvieries
(5) Prodn In Kgs / Hr = (FRD x Fr. rpm x 3.14 x 60 x Effy x Nd) / (Ne x 840 x 36 x
2.2045)
FRD - front roller dia in inches
FRrpm - front roller rpm
effy - efficiency
Ne - Sliver hank
Nd - number of deliveries
SPEEDFRAME + RINGFRAME
(1) Twist / Inch (TPI) = Spindle Speed / FRS
FRS - front roller surface speed in inches/min
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(2) FRS = Fr. rpm x 3.14 x FRD
FRS - Front roller surface speed
FRD - front roller diameter
(3) T.P.I = T.M. x Sqrt (Count or Hank)
T.M. - Twist multiplier
sqrt - square root
(4) Prodn in Kgs / 8 Hrs = (7.2 x SS x Effy) / (TPI x Ne x 1000)
SS - spindle speed
(5) Spindle Speed = M/Min x TPI x 39.37
(6) Hank Delivered = Spindle Speed / ( Tpi x 62.89)
Single yarn strength (gm)
(7) RKM = -----------------------------------
Tex number of yarn
(8) Ring bobbin content = 3.1 LD2 (L = Lift in inch, D = ring dia in inch)
(9) Doubling bobbin content = 3.7 LD2
Actual count x (1 + Present regain)
(10) Corrected count = ------------------------------------------------
1 + Standard regain
Weight per yard of roving fed
(11) Actual draft of ring frame = -----------------------------------------------------------
Weight per yard of yarn delivered on bobbin
Surface speed of front roller
(12) Mechanical draft of ring frame = --------------------------------------
Surface speed of back roller
Draft constant
= --------------------------
Draft change pinion
(13) Twist contraction % = It is basically the percent shortening in length of
yarn between the front roller and the bobbin. The length at the
front roll is taken as 100%. For example 5% twist contraction
means, the yarn length on the bobbin is 95% of the length at the
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front roll.
Yarn count at front roll - yarn count at bobbin
(14) TC% = ------------------------------------------------------------ x 100
Yarn count at front roll
(15) Example of twist contraction given yarn;
Count on bobbin = 10s
Twist contraction = 5%
10 x 1.00
Yarn count at front roll = -------------- = 10.53s
95%
(16) Mechanical draft is always greater than actual draft in ring spinning?
It is necessary to draft the roving to a finer yarn count at front roll that what is to be
bobbin. Because due to twist contraction of yarn, the count of yarn on bobbin becomes
coarser than the count of yarn at front roller.
Twist per inch (TPI)
(17) Twist multiplier or Twist factor = ----------------------------
Ö Count (Ne)
(18) TPI = Twist multiplier x ÖCount (Ne)
or
Twist constant of ring frame
(19) TPI = -------------------------------------
Twist change pinion
(20) Turns per metre (TPM) = Twist factor ÖNm
(21) TPI = TPM x 0.0254
(22) Ring Traveller Speed
Ring Traveller Speed in m/Sec= (Spindle Speed x Ring Dia in mm x 3.14)/
(60 x 1000)
Actual ring traveler speed ?
Assume, spindle speed = 9,000 rpm
Ring Diameter = 57 mm
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Front roll delivery = 64 metre/min.
Package circumference = 102 mm (avg)
Front roll delivery (m/min) x 1000
Traveller lag (rpm) = Spindle speed - ——————————————
Package circumference (mm)
14x1000
= 900 - ———— = 8363 rpm
102
Traveller lag 900 – 8863 = 137 rpm
Uncorrected traveller speed (m/sec.) :
Spindle speed x Ring diameter (mm) x p
= ——————————————————
1000 x 60
9000 x 57 x 3.142
= ——--—————— = 26.8 m/sec.
1000 x 60
Corrected Traveller speed (m/sec.) :
Ring dia (mm) xp x Trav. Lag (rpm)
Traveller speed (m/sec) – —————————————————
60 x 1000
57x 3.142 x 137
= 26.8 - ———————— = 26.39 m/sec.
60 x 1000
(23) Weights of ring travellers No. 1 and 1/0.
For No. 1 = 90 grains / 100 travellers
For No.1/0 = 80 grains/100 travellers
WINDING
1. Slub catcher settings :
a. Fixed Blade = Carded - (2.0 to 2.5) x diameter
Combed - (1.5 to 2.0) x diameter
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b. Electronic yarn clearer = 3 cm x 3 diameter
Diameter in inch = 1/( 28 x Öcount )
for Blended yarn
= 10 to 15% more settings
2. Yarn clearer efficiency = Number of
objectionable thick faults removed by slub catcher
= x 100
Total objectionable thick faults present in yarn before winding
Total breaks during winding (at faults)
3. Knot factor =
No. of breaks due to objectionable yarn faults
Strength of spliced joint x 100
4. Retained splice strength =
Strength of parent yarn
5. Winding Tension = 0.1 x Single yarn strength in grams
4500 x Y
6. Expected efficiency E =
S x N (12 + 98)
7. Winder’s workload (0.17 min/operation on conventional winding m/c = 2300 operations
per shift of 8 hours
where,
1 creeling or 1 piecing = 1 operation
1 doffing = 2 operations
8. Winder’s workload on autoconer (0.08 min per operation) = 4800 operations/shift of 8
hours
where,
1 bobbing feeding = 1 operation
1 doffing (manual) = 4.5 operation
Y = Length/Bobbin (metres)
B = Breaks per bobbin
S = Winding speed (metres/min)
C = English count
(9) Production in Kgs / 8 Hrs = (0.2836 x L x Effy x Nd) / (Ne)
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L - delivery speed in m/min
effy - efficiency
Ne - english count
Nd - No of delvieries
(10) P =( L x 1.0936 x 60 x Effy ) / (Hank (Ne) x 36 x 840 x 2.2045)
P - production in kgs / hr
L - delivery speed in m/min
effy- efficiency
Ne - English count ( number of 840 yards in one pound)
840 - constant
2.2045- to convert from lbs to kilograms
WARPING
R x 100
1. Machine Efficiency E =
R + S
R = Uninterrupted running time for 1,000 meters (in sec)
1000 x 60
=
Machine speed in mtr/min.
S = Total of time in seconds for which the machine is stopped for a production of
1,000 meters
B X N X T1 T2 T3
= R + --------------- + ----- + ---------- + T4
400 L L x C
B = Ends breaks/400 ends/1,000 meters
N = Number of ends
L = Set length in 1,000 meters
C = Beams per creel
Timing of activities in seconds are :
T1 = To mend a break
T2 = To change a beam
T3 = To change a creel
T4 = Miscellaneous Time loss/1,000 mtrs.
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2. Production in metres per 8 hrs. (K) = 480 x mtrs/min x E/100 kgs.
3. Production in Kgs. per 8 hrs. = (K x N)/(1693 x English Count)
4. Warping Tension = 0.03 to 0.05 x Single thread strength
SIZING
Length in metre x 1.094 x Total ends
1. Warp weight = x 100
(in kg.) 840 x 2.204 x Warp count
Sized warp weight - Unsized warp weight
2. Size pick-up = x 100
%age Un-sized warp weight
3. Weight of size = Warp Weight x Size pick up %
Sized warp length - Unsized warp length
4. Stretch %age = x 100
Un-sized warp length
Total-ends x Warp length in yards
5. Sized yarn =
count Sized warp weight (lbs) x 840
Wt. of sized yarn - Wt. of oven dried yarn
6. %age Moisture= x 100
content Wt. of sized yarn
Deliver counter reading - Feed counter reading
7. %age Stretch = x
100 Feed counter reading
840,000 x D x C
8. %age Droppings = x 100
on loom 454 Yx N x P
D = Dropping in gms. C = English Count
Y= Length woven (yds.) N = Number of Ends
P = % size add on
9. Invisible Loss% =
Amount of size material issued - Amount of size added on yarn
= x 100
Amount of size issued
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Steam, Consumption (Sizing M/c) = 2.0 kg/kg of sized yarn
(Cooker) = 0.3 kg/kg of liquor
(Sow box) = 0.2 kg/kg of yarn
No. of Cylinder x 1,000 x English count
10. Max. Speed of machine =
(metres/min) Number of ends
Number of ends x 0.6
11. Wt. of warp in gms/mtr =
English count
WEAVING
1. Reed Count :
It is calculated in stock port system.
EPI
Reed width =
1 + Weft crimp %age
No. of dents in 2 inches is called Reed Count
2. Reed Width :
100 + Weft crimp %age
Reed width = Cloth width x
100
3. Crimp %age :
Warp length - Cloth length
Warp Crimp %age = x 100
Cloth length
Weft length - Cloth length
Weft Crimp %age = x 100
Cloth length
EPI
4. Warp cover factor =
ÖWarp Count
PPI
5. Weft cover factor =
ÖWeft count
Wp.C.F. x Wt. C.F.
6. Cloth cover factor = Wp.C.F. + Wt.C.F. -
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28
7. Maximum EPI for particular count :
a. For plain fabrics = 14 x ÖCount
b. For drill fabrics = ÖCount x 28 x 4/6
c. For satin fabric = ÖCount x 28 x 5/7
Ends/repeat x 1 / yarn diameter
d. Other design =
No. of intersections / repeat + ends/repeat
1
8. Yarn diameter =
28 x ÖCount
Weave Density
1. Warp density = Ends/cm x ÖTex x K
= < 250
2. Filling density = Picks/cm x ÖTex x K
= < 350
(Warp density - 100) x F.D.- 100
3. Weave Density = 50 +
(Weft density - 100) x F.D.- 100
4. Effective weave density = W.D. x K of loom width x K of Design = < 72
To change the count and number of thread/inch, keeping the same denseness of the
fabric :
1. To change the EPI without altering the denseness :
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EPI in given cloth x Ö Warp count in expected cloth
EPI in Exp.Cloth =
Ö Warp count in given cloth
2. To change the count without altering the denseness :
EPI in exp. cloth2
EPI in exp. cloth = x Count in given cloth
EPI in given cloth
Warp requirement to weave a cloth :
Total ends x 1.0936 x 453.59 x crimp%
1. Warp weight in gms/mtrs. = x
Waste 840 x Count %age
2. Weft weight in gms/mtrs. =
R.S. in inches x 453.59 x PPI
= x Crimp %age x Waste %age
840 x Count
Weft wt. in kgs. x Weft count x 1848 x 0.9144
3. Cloth length in mtrs.with =
the given weft weight PPI x R.S. in inches
For Silk and Polyester :
1. Warp weight in gms/mtrs. =
Total ends x Count (Denier)
= x Crimp% x Waste %age
9000
2. Weft weight in gms/mtrs. =
RS in inches x PPI x Count (Denier)
= x Crimp% x Waste %age
9000
Allowance for count in Bleached and Dyed Fabric :
¨ Count becomes 4%
¨ Finer Dyed counts become max.6% Coarser
FABRIC PRODUCTION
14. 10/27/13 TEXTILE CALCULATIONS
file:///D:/textile cal/TEXCALTEXT detail.mht 14/15
Motor pulley diameter
1. Loom speed = Motor RPM x
Loom pulley diameter
Actual production
2. Loom Efficiency %age = ----------------------------- x 100
Calculated production
Yarn weight - Dryed yarn weight
3. Moisture Regain %age = --------------------------------------------- x 100
Dryed yarn weight
Yarn weight - dried yarn weight
4. Moisture Content %age = -------------------------------------------- x 100
Yarn weight
Total ends x Tape length in metre
5. Warp weight in Kg. = ----------------------------------------------
1693.6 x Warp count
RS in centimetres x Coth length in metres x PPI
6. Weft weight in Kg. = ----------------------------------------------------------------
4301.14 x Weft count
EPI PPI
7. Cloth weight in GSM = ----------------- + ----------------- x 25.6
Warp count Weft count
GSM (Grams per sq. metre)
8. Oz (Ounce) per sq.yard = -------------------------------------
34
Material measurement :
For calculating of length of any rolled fabrics :
0.0655 (D - d) (D + d)
L = -------------------------------
t
Where,
L = Length of material (feet)
t = Thickness of fabrics (inches)
D = Outside diameter (inches)
d = Inside diameter (inches)
Weight of yarn in a cloth :
15. 10/27/13 TEXTILE CALCULATIONS
file:///D:/textile cal/TEXCALTEXT detail.mht 15/15
The weight of cloth manufactured on loom depends upon the weight of yarns in the warp and
weft : ends/inch, picks/inch and the weight of size on the warp.
Therefore, Cloth weight = Weight of warp + Weight of weft + Weight of size (All in lbs.)
Total No. of Ends x Tape length in yds.
Where as Weight of warp in lbs = ----------------------------------------------------
840 x Warp yarn count
Also Weight of weft in lbs. =
Length of cloth (yds) x Picks/inch in cloth x Reed width (inch)
= -----------------------------------------------------------------------------------
840 x Weft yarn count